July 2021 has witnessed historically rare, long lasting (> 3 days), and widespread extreme rainfall and severe flooding in central and northern China. This extreme event has left 302 casualties, and direct economic loss of over 100 billion yuan. Zhengzhou, the capital city of Henan Province, received 201.9 mm of rainfall in just one hour on July 20, breaking the record for hourly rainfall rates in the China's land areas. From July 17 to 22, 39 cities in Henan logged rainfall measurements surpassing half of their annual totals, and 10 cities/counties observed rainfall over the 5-day period equivalent to that of an entire year.
Big cities, as the concentrated places for all kinds of resources and socioeconomic activities on multiscales, have urgent and sophisticated needs for meteorological services, and also serve as the most rigorous testbed for these services. In turn, various factors such as increased exposure and vulnerability of meteorological disasters, combined effects of climate change and urbanization, and the initiative for development of safe, green, and smart cities, all present new challenges and opportunities for meteorological support services in big cities.
In recent years, the detection and attribution of extreme weather and climate events has been one of the most cutting-edge scientific issues in the field of climate change research. China has a vast territory and a large population density. The impacts caused by extreme weather and climate events are very serious. However, the current attribution research on major extreme events in China is far from satisfying the increasingly high demands of the public and government on the scientific community. This special issue will concentrate on reporting the most recent research results from studies of heat waves, persistent heavy precipitation, drought, and related compound extreme events in China. The special issue aims to reflect some of the latest developments in research on regional extreme weather and climate events in China, contributing to promote the climate change research in China.
Fengyun Meteorological Satellite Climate Data Records (CDR) Reprocessing：Methods, Products, and Applications
Constructing Climate Data Records (CDR) from satellite historic data is a fundamental work advocated by the Global Climate Observation System (GCOS) programme. Since the launch of the first Fengyun (FY) satellite in 1988, we have collected FY satellite data with a 20-year-long record. Because of the upgrading of the instruments to the same category of instruments, the degradation of the instrument during its lifetime, and the unstable status of the data quality in the early commissioning stage, FY satellite data quality exhibits significant temporal and spatial variations. So far, the archived FY satellite data have never been reprocessed with the state-of-the-art sciences of calibration, cross calibration, and the product algorithms. As a result, neither Fundamental Climate Data Records (FCDR) nor Thematic Climate Data Records (TCDR) have been developed from FY satellites to support the user communities in data reanalysis, and climate and climate change research. In reprocessing the archived data, we need to analyze the historic data quality, characterize the spectral and radiometric response, trace the radiometric benchmark, and harmonize the observations from a series of FY instruments. This special issue will summarize the activities of FY satellite data reprocessing and introduce the current accuracy of FCDR and TCDR. We do hope that this special issue can promote the Chinese satellite data quality and advance their applications in data reanalysis and research on climate and climate change.
Advances in Meteorological Research and Operation Since the Founding of The People’s Republic of ChinaTo celebrate the 70th Anniversary of the People's Republic of China, a special collection of invited papers are published in the Journal of Meteorological Research to reflect the advances in meteorological research and operation since the founding of the PRC. This special collection also intends to document the achievements of China’s meteorological development in the past seven decades.
Since 2014, the Climate Science for Service Partnership China (CSSP China), as a flagship project of the Newton Fund (channeled through the UK-China Research and Innovation Partnership in China), has built a strong foundation for climate science and climate services to support economic development and social welfare in China and the UK by close collaborative work among research experts and user representatives from the China Meteorological Administration’s National Climate Center (CMA NCC) and the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences, the Met Office, and other key UK and Chinese universities, institutes and companies. This special issue will illustrate the rapidly developing capability to develop and deliver climate services in China through progress in science and technology raised by CSSP China.
Research in atmospheric sciences needs high-quality, high-resolution, long-time-series global and regional meteorological data. Unfortunately, neither observational data nor model output alone can satisfy such a requirement. As a promising solution, reanalysis of past observations with a consistent, state-of-the-art numerical model and data assimilation system aims at producing a high-quality climate data, which consists of numerous meteorological variables in a physically consistent and spatiotemporally regular manner. Atmospheric reanalysis products have been widely used in research related to the mechanisms of the earth's climate system, the study of predictability, climate monitoring, and climate change study. China Meteorological Administration (CMA) has started the ReAnalysis project (CRA) of CRA-40 since early 2014, aiming at producing its first-generation 40-yr (1979–2018) global atmosphere and land reanalysis data. In early 2018, a 10-yr (2007–2016) interim product (CRA-Interim) was generated with a 34-km horizontal resolution. More recently, CRA-40 is in production.
Special Issue on Advanced Applications of Meteorological Satellite Observations in Ecological Remote SensingIn past decades, the satellite observations have been widely used for environmental monitoring. In 2018, CMA national ecological remote sensing annual report first time claims that the national vegetation coverage increases 3.7%/year during 2000 to 2017. Meanwhile, the aerosol optical depth and other pollutants declines by 19.3% with respect to the mean of 16 years from 2003 to 2018. On 2/16/2019, NASA also reported the world is getting greener and thanks the tree planning and agriculture in China and India. In the past, there is skepticism that earth greening from satellite observations may be either a result of degradation of satellite instrument performance or stitching of satellite data from a series of instruments. This special issue will present the state-of-the art remote sensing algorithms and satellite products used for the national ecological monitoring. The scientists who are contributing to this special issue are the lead experts in satellite instrument calibration, algorithm developments and product applications.
Land Data Assimilation Systems (LDASs) have gone through almost two decades of research and development where numerous exciting and inspiring progresses have been witnessed. Since the initiation of the North American and Global LDAS (NLDAS and GLDAS) by scientists from the NASA, NOAA, Princeton University, University of Washington, as well as other universities in the beginning of 2000, various national and regional LDASs have been developed in Europe, South America, Canada, and China. These systems have also been extended from offline (uncoupled), semi-coupled, to fully coupled. With satellite products becoming widely and continuously available, LDASs have been largely improved with benefits of data assimilation. At the same time, as more and more in situ and satellite observations become available, the scientific understating of land surface processes and land surface models (LSM) have been greatly improved by addition of more realistic physical processes, optimized model parameters, new soil and vegetation datasets, and upgraded model structures. Improvements in LSM and assimilation of satellite data improved the quality and reliability of LDAS products such that they can be used to provide optimal initial conditions for coupled weather and climate modeling and to support drought monitoring, agricultural crop planning, and water resources management. Many LDAS systems have been operationally implemented at various national service centers to produce timely products to users. Two examples are the NLDAS at NCEP/NOAA and the China Meteorological Administration (CMA) LDAS system (CLDAS for short) at the National Meteorological Information Center (NMIC)/CMA.
Climate system models (CSMs) are essential tools for understanding the mechanisms of climate variability, and predicting and projecting future climate. Due to the complex topography and land-sea distribution, East Asia exhibits distinct climate characteristics, raising a great challenge to the present-day climate models. Most of the climate models still suffer from significant biases in simulating the climate of East Asia, which limits the utilization of these models in understanding the mechanisms of East Asian climate variability as well as in predicting its future changes. In recent years, to meet the demand for climate simulation and prediction in the East Asian region, the Chinese Academy of Meteorological Sciences (CAMS) has been devoted to developing a CSM. By surveying the performance of current CSMs, the CAMS-CSM was established, based on a number of state-of-the-art component models. Some unique features have been incorporated into the CAMS-CSM, such as the treatment of the East Asian topography, the water vapor transport scheme, and the cloud-radiation scheme. The CAMS-CSM has been officially planned to take part in the Coupled Model Intercomparison Project Phase 6 (CMIP6).